The Manticore Project I: a digital twin of our cosmic neighbourhood from Bayesian field-level analysis

TL;DR

The Manticore project introduces a Bayesian simulation suite that creates physically consistent, uncertainty-quantified models of our local cosmic environment, validated against multiple observational metrics and outperforming existing methods.

Contribution

It presents the first full Bayesian posterior ensemble of the local Universe, integrating nonlinear physics and providing detailed uncertainty quantification for cosmic structures.

Findings

Accurately reproduces observed galaxy clusters and their properties.

No significant local underdensity found, consistent with cosmological expectations.

Achieves the highest Bayesian evidence for local velocity fields among tested models.

Abstract

We present the first results from the Manticore project, dubbed Manticore-Local, a suite of Bayesian constrained simulations of the nearby Universe, generated by fitting a physical structure formation model to the 2M++ galaxy catalogue using the BORG algorithm. This field-level inference yields physically consistent realizations of cosmic structure, leveraging a nonlinear gravitational solver, a refined galaxy bias model, and physics-informed priors. The Manticore-Local posterior realizations evolve within a parent cosmological volume statistically consistent with LCDM, demonstrated through extensive posterior predictive tests of power spectra, bispectra, initial condition Gaussianity, and the halo mass function. The inferred local supervolume shows no significant deviation from cosmological expectations; notably, we find no evidence for a large local underdensity. Our model identifies high-significance counterparts for fourteen prominent galaxy clusters each within one degree of its observed sky position. Across the posterior ensemble, these counterparts are consistently detected with 2-4 sigma significance, and their reconstructed masses and redshifts agree closely with observational estimates, confirming the inference's spatial and dynamical fidelity. The peculiar velocity field recovered by Manticore-Local achieves the highest Bayesian evidence across five datasets, surpassing state-of-the-art models. Unlike methods yielding only point estimates or using simplified dynamics, Manticore-Local provides a full Bayesian posterior over cosmic structure and evolution, enabling rigorous uncertainty quantification. These results establish Manticore-Local as the most advanced constrained realization suite of the Local Universe to date, offering a robust statistical foundation for future studies of galaxy formation, velocity flows, and environmental dependencies in our cosmic neighbourhood.